11
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Nonmonotone Adaptive Barzilai-Borwein Gradient Algorithm for Compressed Sensing

      , ,
      Abstract and Applied Analysis
      Hindawi Limited

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          We study a nonmonotone adaptive Barzilai-Borwein gradient algorithm for l 1 -norm minimization problems arising from compressed sensing. At each iteration, the generated search direction enjoys descent property and can be easily derived by minimizing a local approximal quadratic model and simultaneously taking the favorable structure of the l 1 -norm. Under some suitable conditions, its global convergence result could be established. Numerical results illustrate that the proposed method is promising and competitive with the existing algorithms NBBL1 and TwIST.

          Related collections

          Most cited references21

          • Record: found
          • Abstract: not found
          • Article: not found

          Atomic Decomposition by Basis Pursuit

            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Smooth minimization of non-smooth functions

              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Gradient Projection for Sparse Reconstruction: Application to Compressed Sensing and Other Inverse Problems

                Bookmark

                Author and article information

                Journal
                Abstract and Applied Analysis
                Abstract and Applied Analysis
                Hindawi Limited
                1085-3375
                1687-0409
                2014
                2014
                : 2014
                :
                : 1-6
                Article
                10.1155/2014/410104
                b24a3277-972a-4284-a25b-9a6cd79f982d
                © 2014

                http://creativecommons.org/licenses/by/3.0/

                History

                Comments

                Comment on this article